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Data-Driven Controllability Analysis and Stabilization for Linear Descriptor Systems

2021/12/07 by Jiabao He, He, Jiabao, Xuan Zhang +5 · 1 citation
Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #Fault Detection and Control Systems #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2112.03665

openalex publication_date 2021/12/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

For a parameter-unknown linear descriptor system, this paper proposes data-driven methods to testify the system's type and controllability and then to stabilize it. First, a data-based condition is developed to identify whether this unknown system is a descriptor system or is equivalent to a normal system. Furthermore, various controllability concepts are testified by replacing the descriptor system's matrices with data. Finally, a data-based decomposing method is proposed to transfer the nominal system into its slow-fast subsystems' form, so that a state feedback controller for the slow subsystem can be obtained from persistently exciting input and state sequences. Meanwhile, due to the equivalent stabilizability between the nominal system and its slow subsystem, a state feedback controller which stabilizes the nominal system is also obtained. A simulation example is provided to illustrate the effectiveness of those methods.

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